• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.5
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• pp.343-356
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• 1991

An efficient real-time implementation of digital filtering algorithms using a multiprocessor system in a ring network is investigated. The development time and cost for implementing a high speed signal processing system can be considerably reduced because algorithm are implemented in software using commercially available digital signal processors. This method is based on a parallel block processing approach, where a continuously supplied input data is divided into blocks, and the blocks are processed concurrently by being assigned to each processor in the system. This approach not only requires a simple interconnection network but also reduces the number of communications among the processors very much. The data dependency of the blocks to be processed concurrently brings on dependency problems between the processors in the system. A systematic scheduling method has been developed by using a processors which can be used efficiently, the methods for solving dependency problems between the processors are investigated. Implementation procedures and results for FIR, recursive (IIR), and adaptive filtering algorithms are illustrated.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.10
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• pp.1109-1116
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• 1992

Mathematical morphology, theoretical foundation for morphological filter, is very efficient for the analysis of the geometrical characteristics of signals and systems and is used as a predominant tool for smoothing the data with noise. In this study, H/W design of morphological filter is implemented to process the gray scale dilation and the erosion in the same circuit and to choose the maximum and minimum value by a selector, resulting in their education of the complexity of the circuit and an architecture for parallel processing. The structure of morphological filter consists of the structuring-element block, the image data block, the control block, the ADD block, the MIN/MAX block, etc, and is designed on an one-chip for real time operation.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1042-1047
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• 2004

Voltage control is an essential part of the electric energy transmission and distribution system to maintain proper voltage limit at the consumer's terminal. Besides the generating units that provide the basic voltage control, there are many additional voltage-controlling agents e.g., shunt capacitors, shunt reactors, static VAr compensators, regulating transformers mentioned in [1], [2]. The most popular one, among all those agents for controlling voltage levels at the distribution and transmission system, is the on-load tap changer transformer. It serves two functions-energy transformation in different voltage levels and the voltage control. Artificial Neural Network (ANN) has been realized as a convenient tool that can be used in controlling the on load tap changer in the distribution transformers. Usage of the ANN in this area needs suitable training and testing data for performance analysis before the practical application. This paper briefly describes a procedure of processing the data to train an Artificial Neural Network (ANN) to control the tap changer operating decision of parallel transformers for a closed primary bus. The data set are used to train a two layer ANN using three different neural net learning algorithms, namely, Standard Backpropagation [3], Bayesian Regularization [4] and Scaled Conjugate Gradient [5]. The experimental results are presented including performance analysis.

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.513-516
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• 2007

Because many scientific applications require large data processing, the importance of parallel I/O has been increasingly recognized. Collective I/O is one of the considerable features of parallel I/O and enables application programmers to easily handle their large data volume. In this paper we measure and analyze the performance of original collective I/Os and the subgroup method, the way of using collective I/O of MPI effectively. From the experimental results, we found that the two kinds of subgroup method showed different performance. In terms of collective write operation, the subgroup method caused the performance degradation. However, the subgroup method for collective read showed good performance with small data size.

• The KIPS Transactions:PartA
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• v.8A no.2
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• pp.117-124
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• 2001

At NOW (Networks Of Workstations), the load sharing is very important role for improving the performance. The known load sharing strategy is fixed-granularity, variable-granularity and adaptive-granularity. The variable-granularity algorithm is sensitive to the various parameters. But Send algorithm, which implements the fixed-granularity strategy, is robust to task granularity. And the performance difference between Send and variable-granularity algorithm is not substantial. But, in Send algorithm, the computing time and the communication time are not overlapped. Therefore, long latency time at the network has influence on the execution time of the parallel program. In this paper, we propose the preSend algorithm. In the preSend algorithm, the master node can send the data to the slave nodes in advance without the waiting for partial results from the slaves. As the master node sent the next data to the slaves in advance, the slave nodes can process the data without the idle time. As stated above, the preSend algorithm can overlap the computing time and the communication time. Therefore we reduce the influence of the long latency time at the network and the execution time of the parallel program on the NOW. To compare the execution time of two algorithms, we use the $320{\times}320$ matrix multiplication. The comparison results of execution times show that the preSend algorithm has the shorter execution time than the Send algorithm.

• Journal of the Optical Society of Korea
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• v.17 no.5
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• pp.362-370
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• 2013

In this paper, we propose a novel optical implementation of a 3DES algorithm based on dual XOR logic operations for a cryptographic system. In the schematic architecture, the optical 3DES system consists of dual XOR logic operations, where XOR logic operation is implemented by using a free-space interconnected optical logic gate method. The main point in the proposed 3DES method is to make a higher secure cryptosystem, which is acquired by encrypting an individual private key separately, and this encrypted private key is used to decrypt the plain text from the cipher text. Schematically, the proposed optical configuration of this cryptosystem can be used for the decryption process as well. The major advantage of this optical method is that vast 2-D data can be processed in parallel very quickly regardless of data size. The proposed scheme can be applied to watermark authentication and can also be applied to the OTP encryption if every different private key is created and used for encryption only once. When a security key has data of $512{\times}256$ pixels in size, our proposed method performs 2,048 DES blocks or 1,024 3DES blocks cipher in this paper. Besides, because the key length is equal to $512{\times}256$ bits, $2^{512{\times}256}$ attempts are required to find the correct key. Numerical simulations show the results to be carried out encryption and decryption successfully with the proposed 3DES algorithm.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.339-345
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• 2022

Outcome-based education (OBE) is a tried-and-true teaching technique based on a set of predetermined goals. Program Educational Objectives (PEOs), Program Outcomes (POs), and Course Outcomes (COs) are the components of OBE. At the end of each year, the Program Outcomes are evaluated, and faculty members can submit many recommended measures which dependent on the relationship between the program outcomes and its courses outcomes to improve the quality of program and hence the overall educational program. When a vast number of courses are considered, bad actions may be proposed, resulting in unwanted and incorrect decisions. In this paper, a recommender system, using collaborative filtering and association rules algorithms, is proposed for predicting the best relationship between the program outcomes and its courses in order to improve the attributes of the graduates. First, a parallel algorithm is used for Collaborative Filtering on Data Model, which is designed to increase the efficiency of processing big data. Then, a parallel similar learning outcomes discovery method based on matrix correlation is proposed by mining association rules. As a case study, the proposed recommender system is applied to the Computer Information Systems program, College of Computer Sciences and Information Technology, Al-Baha University, Saudi Arabia for helping Program Quality Administration improving the quality of program outcomes. The obtained results revealed that the suggested recommender system provides more actions for boosting Graduate Attributes quality.

• International Journal of Aeronautical and Space Sciences
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• v.4 no.1
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• pp.34-44
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• 2003

An advanced aeroelastic analysis using a computational structural dynamics (CSD), finite element method (FEM) and computational fluid dynamics (CFD) is presented in this Paper. A general aeroelastic analysis system is originally developed and applied to realistic design problems in the transonic flow region, where strong shock wave interactions exist. The present computational approach is based on the modal-based coupled nonlinear analysis with the matched-point concept and adopts the high-speed parallel processing technique on the low-cost network based PC-clustered machines. It can give very accurate and useful engineering data on the structural dynamic design of advanced flight vehicles. For the nonlinear unsteady aerodynamics in high transonic flow region, Euler equations using the unstructured grid system have been applied to easily consider complex configurations. It is typically shown that the advanced numerical approach can give very realistic and practical results for design engineers and safe flight tests. One can find that the present study conducts a virtual flutter flight test which are usually very dangerous in reality.

• The Transactions of the Korea Information Processing Society
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• v.7 no.3
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• pp.776-787
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• 2000

Write requests which stored in disk cache of the RAID5 controller should be destaged to disk arrays according to the destage algorithm. As the response performance of the parallel IO request is being hit by the effect of the destage, several destage algorithms have been studied to enhance the performance of he RAID5 controller. Among the destage algorithms, the load balancing destage algorithm has better performance than other destage algorithms when system load is highly increased. But the load balancing destage algorithm gives priority to load balance among the disks in disk arrays, therefore, when some disks are affected by the very heavy system load caused by small data requests, the load balancing destage algorithm cannot enhance the performance of parallel IO requests effectively since it makes effort to maintain the load balance without the benefit of the locality of the write requests. This paper proposes a new RAID5 controller that applied reference-load balancing destage algorithm which decides the destage priority based on the reference history and load distribution of the disks. The simulation results show that RAID5 controller with the reference-load balancing destage algorithm has better performance than previous load balancing destage algorithm.

• Annual Conference of KIPS
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• 2023.05a
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• pp.389-391
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• 2023

In the era of Big Data, humanity is facing a huge overflow of information. To overcome such an obstacle, many new cutting-edge technologies are being introduced. The movie recommendation system is also one such technology. To date, many theoretical and practical kinds of research have been conducted. Our research also focuses on the movie recommendation system by implementing methods from Social Network Analysis(SNA) and Parallel Programming. We applied the Girvan-Newman algorithm to detect communities of users, and a future package to perform the parallelization. This approach not only tries to improve the accuracy of the system but also accelerates the execution time. To do our experiment, we used the MovieLense Dataset.